OBJECTIVE: Both the duration of sexual partnerships and the time between two consecutive partnerships (gap length) varies between populations. We use a mathematical model with multiple partnership durations and gap lengths to identify the types of relationship cycles that sustain gonorrhea transmission in the United Kingdom. STUDY DESIGN: A mathematical model for gonorrhea transmission was constructed which tracks the duration of partnerships and their preceding gap lengths. The National Survey of Sexual Attitudes and Lifestyles was used to parameterize the model population into 5 different partnership lengths (mean of 1 day, 2 weeks, 8 weeks, 30 weeks, and 10 years) and 3 preceding gap lengths (14 days, 8 weeks, and 1.5 years). RESULTS: The model was able to reproduce patterns of gonococcal infection in the United Kingdom. Assortative (like-with-like) mixing of individuals with short gaps between partnerships was required for gonorrhea infection to persist. Prevalence was highest in individuals with short (>1 day-<1 month) and midterm partnership durations (>1 month-<3 months). Interventions (such as increased condom use) targeted at those with medium-term partnerships were most effective at reducing prevalence; in contrast targeting interventions at those with short partnerships but longer gap lengths (i.e., the group with the highest number of sexual partners) had relatively less impact. CONCLUSION: Our model suggests that gonorrhea is sustained by the presence of a small group of individuals with short gap lengths and medium length partnerships. Interventions targeted at this group are more effective than those targeted at individuals with high numbers of sexual partners but longer gap lengths.
OBJECTIVE: Both the duration of sexual partnerships and the time between two consecutive partnerships (gap length) varies between populations. We use a mathematical model with multiple partnership durations and gap lengths to identify the types of relationship cycles that sustain gonorrhea transmission in the United Kingdom. STUDY DESIGN: A mathematical model for gonorrhea transmission was constructed which tracks the duration of partnerships and their preceding gap lengths. The National Survey of Sexual Attitudes and Lifestyles was used to parameterize the model population into 5 different partnership lengths (mean of 1 day, 2 weeks, 8 weeks, 30 weeks, and 10 years) and 3 preceding gap lengths (14 days, 8 weeks, and 1.5 years). RESULTS: The model was able to reproduce patterns of gonococcal infection in the United Kingdom. Assortative (like-with-like) mixing of individuals with short gaps between partnerships was required for gonorrhea infection to persist. Prevalence was highest in individuals with short (>1 day-<1 month) and midterm partnership durations (>1 month-<3 months). Interventions (such as increased condom use) targeted at those with medium-term partnerships were most effective at reducing prevalence; in contrast targeting interventions at those with short partnerships but longer gap lengths (i.e., the group with the highest number of sexual partners) had relatively less impact. CONCLUSION: Our model suggests that gonorrhea is sustained by the presence of a small group of individuals with short gap lengths and medium length partnerships. Interventions targeted at this group are more effective than those targeted at individuals with high numbers of sexual partners but longer gap lengths.
Authors: Bart Burington; James P Hughes; William L H Whittington; Brad Stoner; Geoff Garnett; Sevgi O Aral; King K Holmes Journal: Sex Transm Infect Date: 2010-04 Impact factor: 3.519
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Authors: Christian L Althaus; Katherine M E Turner; Boris V Schmid; Janneke C M Heijne; Mirjam Kretzschmar; Nicola Low Journal: J R Soc Interface Date: 2011-06-08 Impact factor: 4.118
Authors: Meghan D Althoff; Colin Anderson-Smits; Stephanie Kovacs; Oscar Salinas; John Hembling; Norine Schmidt; Patricia Kissinger Journal: AIDS Behav Date: 2013-09
Authors: Irene A Doherty; Marc L Serre; Dionne Gesink; Adaora A Adimora; Stephen Q Muth; Peter A Leone; William C Miller Journal: Epidemiology Date: 2012-11 Impact factor: 4.822